Proteogenomics: Key Driver for Clinical Discovery and Personalized Medicine
Ruggero Barbieri1, Victor Guryev2, Corry-Anke Brandsma3
1Department of Gastroenterology and Hepatology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Advances in Experimental Medicine and Biology
|October 1, 2016
Summary
Proteogenomics integrates genomics, transcriptomics, and proteomics to discover patient-specific protein variants. This multi-omics approach enhances understanding of disease mechanisms and advances precision medicine in cancer research.
Area of Science:
- Biochemistry
- Genomics
- Proteomics
- Multi-omics Research
Background:
- Proteogenomics integrates genomics, transcriptomics, and proteomics to bridge molecular layers.
- Understanding genomic mutations' impact on proteome is crucial for disease insights.
- Current proteomics methods may not fully capture patient-specific molecular variations.
Purpose of the Study:
- To explore the integration of genomics, transcriptomics, and proteomics through a proteogenomics approach.
- To identify novel patient-specific proteoforms relevant to disease development, particularly in cancer.
- To elucidate molecular mechanisms of disease by analyzing persistent changes across multiple molecular layers.
Main Methods:
- Multi-omics data integration (genomics, transcriptomics, proteomics).
- Analysis of single nucleotide polymorphisms (SNPs) and their impact on transcript and protein expression.
- Bioinformatics and technological aspects of sample preparation, data acquisition, and processing.
Main Results:
- Identification of patient-specific proteoforms with potential implications in cancer.
- Enhanced interpretation of molecular mechanisms underlying disease.
- Demonstration of persistent molecular changes across genomics, transcriptomics, and proteomics.
Conclusions:
- Proteogenomics enables a comprehensive understanding of disease at multiple molecular levels.
- This approach facilitates the identification of patient-specific protein alterations for personalized medicine.
- The study provides guidance on technological and bioinformatics challenges in proteogenomics applications.
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